Voyager Alternatives

Voyager reviews and mentions

• Project Sid: Many-agent simulations toward AI civilization
  2 projects | news.ycombinator.com | 3 Nov 2024

  > LLMs are stateless and they do not remember the past (as in they don't have a database), making the training data a non-issue here.

  That's not what they said. They said that a LLM knows what elections are, which suggests they could have the requisite knowledge to act one out.

  > Therefore, the claims made here in this paper are not possible because the simulation would require each agent to have a memory context larger than any available LLM's context window. The claims made here by the original poster are patently false.

  No, it doesn't. They aren't passing in all prior context at once: they are providing relevant subsets of memory as context. This is a common technique for language agents.

  > Agentic systems are not well-suited to achieve any of the things that are proposed in the paper, and Generative AI does not enable these kinds of advancements.

  This is not new ground. Much of the base social behaviour here comes from Generative Agents [0], which they cite. Much of the Minecraft related behaviour is inspired by Voyager [1], which they also cite.

  There isn't a fundamental breakthrough or innovation here that was patently impossible before, or that they are lying about: this combines prior work, iterates upon it, and scales it up.

  [0]: https://arxiv.org/abs/2304.03442

  [1]: https://voyager.minedojo.org/

• We no longer use LangChain for building our AI agents
  10 projects | news.ycombinator.com | 20 Jun 2024

  Some "agents" like the minecraft bot Voyager(https://github.com/MineDojo/Voyager) have a control loop, they are given a high level task and then they use LLM to decide what actions to take, then evaluate the result and iterate. In some LLM frameworks, a chain/pipeline just uses LLM to process input data(classification, named entitiy extraction, summary, etc).

• Google Launches Gemini, Its "Most Powerful" AI Model to Date
  2 projects | /r/Futurology | 10 Dec 2023

  Source: Conversation with Bing, 12/10/2023 (1) Wes Roth - YouTube. https://www.youtube.com/@WesRoth. (2) I've set most of my videos to Public again - Community. https://community.openai.com/t/ive-set-most-of-my-videos-to-public-again/24535. (3) AI Updates: Meta Develops Mind-Reading AI System, OpenAI’s Q* Is Here .... https://www.windermeresun.com/2023/11/20/ai-updates-meta-develops-mind-reading-ai-system-openais-q-is-here-how-economy-will-work-after-agi/. (4) David Shapiro. https://www.daveshap.io/. (5) undefined. https://natural20.com/. (6) undefined. https://arxiv.org/abs/2305.16291. (7) undefined. https://twitter.com/DrJimFan/status/1. (8) undefined. https://voyager.minedojo.org/. (9) undefined. https://minedojo.org/. (10) undefined. https://www.youtube.com/@DavidShapiroAutomator/videos.

• Is there any game that allow us to interact with it by python?
  2 projects | /r/reinforcementlearning | 1 Dec 2023
• A Coder Considers the Waning Days of the Craft
  2 projects | news.ycombinator.com | 13 Nov 2023

  > AI cannot sustain itself trained on AI work.

  This isn’t true. You can train LLMs entirely on synthetic data and get strong results. [0]

  > If new languages, engines etc pop up it cannot synthesize new forms of coding without that code having existed in the first place.

  You can describe the semantics to a LLM, have it generate code, tell it what went wrong (i.e. with compiler feedback), and then train on that. For an example of this workflow in a different context, see [1].

  > And most importantly, it cannot fundamentally rationalize about what code does or how it functions.

  Most competent LLMs can trivially describe what some code does and speculate on the reasoning behind it.

  I don’t disagree that they’re flawed and imperfect, but I also do not think this is an unassailable state of affairs. They’re only going to get better from here.

  [0]: https://arxiv.org/abs/2309.05463

  [1]: https://voyager.minedojo.org/

• AutoGen: Enable Next-Gen Large Language Model Applications
  4 projects | news.ycombinator.com | 18 Oct 2023

  In a way it is the same thing, agents are mostly an abstraction that make it easier to know what’s going on.

  I think of agents more or less as python classes with a mixture of natural language and code functions. You design them to do something with information they produce, and to interface with other agents or “tools” in some way.

  But all the agents can be the same language model under the hood, they are frames used to build different kinds of contexts.

  And yes I think the idea is that emergent behaviour can be useful. This comes to mind

  https://github.com/MineDojo/Voyager

  But I think we are still a small ways off from being really smart about agents. My opinion is that we haven’t quite figured out what we are doing yet.

• Open/Local LLM support for MineDojo/Voyager
  4 projects | /r/LocalLLaMA | 11 Oct 2023

  This k8s application deploys an instance of Voyager along with a Fabric Minecraft server with required fabric mods. It assumes you have a local deployment of a Large Language Model (LLM) with 4K-8K token context length with a compatible OpenAI API, including embeddings support.

• Voyager – Minecraft Embodied Agent with Large Language Models
  1 project | news.ycombinator.com | 17 Sep 2023
• List of Awesome AI Agents like AutoGPT and BabyAGI / Many open-source Agents with code included!
  6 projects | /r/singularity | 12 Aug 2023

  In my opinion the most interesting Agents: Auto-GPT Github: https://github.com/Significant-Gravitas/Auto-GPT BabyAGI Github: https://github.com/yoheinakajima/babyagi Voyager Github: https://github.com/MineDojo/Voyager / Paper: https://arxiv.org/abs/2305.16291 I would also add: ChemCrow: Augmenting large-language models with chemistry tools Github: https://github.com/ur-whitelab/chemcrow-public/ Paper: https://arxiv.org/abs/2304.05376

• [D] - Are there any AI benchmarks that involve successful longterm problem solving when running as autonomous agents (like in autogpt)? How do we compare the effectiveness of models as agents?
  1 project | /r/MachineLearning | 9 Jul 2023

  Does this beat the voyager? I read about it and wondered what if we add a skill library to langchain/llamaindex agents. It could be the same vector store for storing static data but after each task is performed, the agent will evaluate and archive the recipe of steps to perform a new task. Next time when the agent is asked to perform a task, it can just look at the library to retrieve a recipe. Unlike traditional fine tuning, you dont update the model parameters, these recipes are much more interpretable and can be manually edited/inserted by humans. There may also be an automatic way to convert wikihow articles or youtube tutorials into recipes.

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